TRANSLATING RESEARCH BACK TO THE COMMUNITY: FINDINGS FROM A REALIST REVIEW
Bibliographic record
Abstract
This presentation will report on the process of conducting a realist synthesis review as part of a larger integrated knowledge translation (KT) project to assess gaps in information and communication technology (ICT) use among middle-aged and older adults. The realist review method is used to examine and understand causal mechanisms, exploring what works, for whom, in what circumstances, and why. To enhance this review, we applied an intersectional framework when synthesizing the evidence (i.e., peer-reviewed and grey literature) on access to and use of ICTs to better understand ways in which inequities exist. Review findings were shared with knowledge users at two World Café events, which enriched the realist review by validating some areas of the review, while also offering avenues for further refinement of the research. Such KT methods are integral to informing and enhancing service and technology development for seniors and will be detailed in this presentation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.169 | 0.433 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".